ed175d6d92
### What this PR does / why we need it? This PR adds the releaseing note skills: - `SKILL.md`: vLLM Ascend Releasing Note Writer - `references/ref-past-release-notes-highlight.md`: And also add a `output/v0.13.0` examples which was used by2da476d82fInspired: https://github.com/simon-mo/release-notes-writing/ ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? - vLLM version: v0.15.0 - vLLM main:83b47f67b1Co-authored-by: esmeetu <jasonailu87@gmail.com> --------- Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
116 lines
4.7 KiB
Markdown
116 lines
4.7 KiB
Markdown
# vLLM Ascend skills
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This directory contains the skills for vLLM Ascend.
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Note: Please copy the skills directory `.agents/skills` to `.claude/skills` if you want to use the skills in this repo with Claude code.
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## Table of Contents
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- [vLLM Ascend Model Adapter Skill](#vllm-ascend-model-adapter-skill)
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- [vLLM Ascend main2main Skill](#vllm-ascend-main2main-skill)
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- [vLLM Ascend Release Note Writer Skill](#vllm-ascend-release-note-writer-skill)
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## vLLM Ascend Model Adapter Skill
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Adapt and debug models for vLLM on Ascend NPU — covering both already-supported
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architectures and new models not yet registered in vLLM.
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### What it does
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This skill guides an AI agent through a deterministic workflow to:
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1. Triage a model checkpoint (architecture, quant type, multimodal capability).
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2. Implement minimal code changes in `/vllm-workspace/vllm` and `/vllm-workspace/vllm-ascend`.
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3. Validate via a two-stage gate (dummy fast gate + real-weight mandatory gate).
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4. Deliver one signed commit with code, test config, and tutorial doc.
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### File layout
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| File | Purpose |
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| ---- | ------- |
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| `SKILL.md` | Skill definition, constraints, and execution playbook |
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| `references/workflow-checklist.md` | Step-by-step commands and templates |
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| `references/troubleshooting.md` | Symptom-action pairs for common failures |
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| `references/fp8-on-npu-lessons.md` | FP8 checkpoint handling on Ascend |
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| `references/multimodal-ep-aclgraph-lessons.md` | VL, EP, and ACLGraph patterns |
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| `references/deliverables.md` | Required outputs and commit discipline |
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### Quick start
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1. Open a conversation with the AI agent inside the vllm-ascend dev container.
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2. Invoke the skill (e.g. `/vllm-ascend-model-adapter`).
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3. Provide the model path (default `/models/<model-name>`) and the originating issue number.
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4. The agent follows the playbook in `SKILL.md` and produces a ready-to-merge commit.
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### Key constraints
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- Never upgrade `transformers`.
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- Start `vllm serve` from `/workspace` (direct command, port 8000).
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- Dummy-only evidence is not sufficient — real-weight validation is mandatory.
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- Final delivery is exactly one signed commit in the current repo.
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### Two-stage validation
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- **Stage A (dummy)**: fast architecture / operator / API path check with `--load-format dummy`.
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- **Stage B (real)**: real-weight loading, fp8/quant path, KV sharding, runtime stability.
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Both stages require request-level verification (`/v1/models` + at least one chat request),
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not just startup success.
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## vLLM Ascend main2main Skill
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Migrate changes from the main vLLM repository to the vLLM Ascend repository, ensuring compatibility and performance optimizations for Ascend NPUs.
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### What it does
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This skill facilitates the process of:
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1. Identifying changes in the main vLLM repository.
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2. Applying necessary modifications for Ascend support.
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3. Validating the changes in an Ascend environment.
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4. Delivering a ready-to-merge commit with optimized code and configurations.
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### Quick start
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1. Open a conversation with the AI agent inside the vllm-ascend dev container.
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2. Invoke the skill (e.g. `/main2main`).
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3. The agent follows the playbook and produces a ready-to-merge commit.
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## vLLM Ascend Release Note Writer Skill
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You just need to say: `Please help me write a 0.13.0 release note based on commits from v0.11.0 and releases/v0.13.0`
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### What it does
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This skill guides you through a structured workflow to:
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1. Fetch commits between two versions using the provided script.
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2. Analyze and categorize each commit in a CSV workspace.
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3. Draft highlights and write polished release notes.
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4. Generate release notes organized by category (Features, Hardware Support, Performance, Dependencies, etc.).
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### File layout
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| File | Purpose |
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| ---- | ------- |
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| `SKILL.md` | Skill definition, workflow, and writing guidelines |
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| `references/ref-past-release-notes-highlight.md` | Style and category reference for release notes |
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| `scripts/fetch_commits-optimize.py` | Script to fetch commits between versions |
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### Quick start
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1. Open a conversation with the AI agent.
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2. Invoke the skill (e.g. `/vllm-ascend-release-note-writer`).
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3. Follow the workflow steps:
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- Fetch commits between versions
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- Analyze commits in CSV format
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- Draft and edit highlights
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4. Output files are saved to `vllm-ascend-release-note/output/$version`
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### Key guidelines
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- Use one-level headings (###) for sections in a specific order: Highlights, Features, Hardware and Operator Support, Performance, Dependencies, Deprecation & Breaking Changes, Documentation, Others.
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- Focus on user-facing impact and include context for practical usage.
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- Verify details by checking linked PRs (use GitHub API for descriptions if needed).
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- Keep notes concise and avoid unnecessary technical details.
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